Title: BI Cloud Datawarehouse Developer II
Location: Midtown
Org Unit: Business Intelligence
Work Days:
Weekly Hours: 35.00
Exemption Status: Exempt
Salary Range: $125,400.00 - $140,400.00
- As required under NYC Human Rights Law Int 1208-2018 - Salary range for this role when Hired for NYC Offices
The Senior Cloud Data Engineer plays a key role in designing, developing, and implementing large-scale cloud data solutions to support the institution’s Business Intelligence and analytics needs. This position is responsible for architecting and building scalable data integration, processing, and storage solutions across platforms such as Amazon Redshift, Snowflake, and Azure. The engineer develops robust data pipelines using Azure technologies and enterprise ETL tools including Informatica Intelligent Data Management Cloud (IDMC), SAP Data Services (BODS), SSIS, and Azure Data Factory. The Senior Cloud Data Engineer drives the creation of high-quality, well-governed datasets by ensuring strong data quality practices, supporting Master Data Management (MDM) initiatives, and implementing data governance and cataloging capabilities. The role encompasses all phases of database and data engineering project work—from requirements gathering and data modeling to testing, deployment, and optimization. This position requires deep experience with cloud data architectures, enterprise ETL platforms, and modern BI ecosystems, including the Microsoft BI Stack (SSIS/Data Factory, Azure Data Warehouse, Azure Analytics/SSAS, and Power BI). The engineer also designs and delivers integrated solutions leveraging SAP Business Warehouse (BW), SAP Data Services, Workday, and Workday Prism. This role ensures the delivery of reliable, scalable, and high-performance data solutions that support the institution’s reporting, analytics, and strategic decision-making needs.
- Design and implement data migration, ingestion, and integration strategies, including Data Lake and multidimensional data modeling within Amazon Redshift, Snowflake, and Azure.
- Translate business requirements into scalable data models that drive Data Lakes and Data Warehouse architectures.
- Collaborate with cross-functional teams to gather, document, and validate business requirements for analytics and reporting initiatives.
- Build and maintain data ingestion pipelines for batch and real-time data movement, including CDC from cloud and on-premises applications into Data Lakes or raw zones.
- Design, develop, optimize, and support cloud data pipelines using Azure Data Factory, Azure Spark, AWS Glue, Snowpark, and SAP BODS.
- Transform unstructured and disparate data sources into curated datasets for Data Stores, Data Lakes, and Data Warehouses.
- Model data to support diverse reporting and analytics needs across cloud platforms such as Redshift, Azure Synapse, Google BigQuery, and Snowflake.
- Identify data gaps and build new pipelines and automated processes to deliver enriched, high-quality datasets for enterprise applications and analytics.
- Partner with administrators and architects to design, configure, and secure Power BI solutions, including gateways, Azure integrations, and data connectors.
- Develop, maintain, and optimize dashboards, paginated reports, custom visuals, and analytics solutions using Power BI, DAX, SQL, and SQL Server.
- Build reporting and BI solutions leveraging SAP BW, SAP Data Services (BODS), Workday, and Workday Prism.
- Design and implement ETL/ELT workflows using Informatica IDMC, SAP BODS, SSIS, and Azure Data Factory.
- Develop integrations and reporting solutions across enterprise platforms including SAP, Workday/Prism, Redshift, Snowflake, SQL Server, and other data sources.
- Review, tune, and optimize data models, pipelines, and applications to improve performance, scalability, and reliability.
- Recommend best practices and enhancements to improve overall system efficiency and architecture quality.
- Support Master Data Management (MDM) initiatives and enforce data governance, cataloging, and metadata management standards.
- Ensure data consistency, quality, and stewardship across enterprise data platforms.
- Provide technical mentoring to team members on cloud technologies, data engineering best practices, and modern data architectures.
- Work closely with stakeholders, architects, and administrators to ensure end-to-end solution alignment and architectural integrity.
- Bachelor's Degree in Computer Science or related field preferred; equivalent work experience will be considered.
- 5–10 years of experience designing and delivering data warehouse and cloud data solutions.
- Hands-on experience with AWS Redshift, Snowflake, Azure Data Lake, Azure Data Factory, Synapse Analytics, Delta tables, and multi-layered data lake architectures.
- Experience with data migration from on-premises or cloud systems to cloud data warehouses.
- Experience with Informatica Intelligent Data Management Cloud (IDMC).
- Experience developing complex SQL queries and stored procedures.
- Experience with Python or Scala preferred.
- Power BI experience is a plus.
- Familiarity with Agile/Scrum environments.
- Certifications in Azure or AWS technologies are desirable.
- Deep knowledge of cloud data architecture, data ingestion, transformation, and storage best practices.
- Strong analytical and problem-solving skills; ability to troubleshoot complex data issues.
- Ability to translate business requirements into actionable technical solutions.
- Excellent verbal and written communication skills.
- Collaborative mindset and ability to work effectively with cross-functional teams.
- Knowledge of SAP Finance/HCM modules and research administrative systems (e.g., InfoEd) is a plus.
- Commitment to continuous learning and professional development in cloud data technologies.
- Desire to work in a highly collaborative environment
- Position requires working in an office environment where there some physical discomforts such as dust, dirt, noise, and the like are present. Ability to work off-hours and weekends for go-lives, testing and emergencies, as well as travel between office locations, primarily within NYC is required. Occasional meetings or clinical staff interactions in typical patient care areas may be required though direct patient exposure is not expected. Occasional moving of computer equipment or similar objects up to approximately 50lbs may be required to expedite projects.
Cornell welcomes students, faculty, and staff with diverse backgrounds from across the globe to pursue world-class education and career opportunities, to further the founding principle of “any person, any study.” No person shall be denied employment on the basis of any legally protected status or subjected to prohibited discrimination involving, but not limited to, such factors as race, ethnic or national origin, citizenship and immigration status, color, sex, pregnancy or pregnancy-related conditions, age, creed, religion, actual or perceived disability (including persons associated with such a person), arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual’s genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law.
Cornell University embraces diversity in its workforce and seeks job candidates who will contribute to a climate that supports students, faculty, and staff of all identities and backgrounds. We hire based on merit, and encourage people from historically underrepresented and/or marginalized identities to apply. Consistent with federal law, Cornell engages in affirmative action in employment for qualified protected veterans as defined in the Vietnam Era Veterans’ Readjustment Assistance Act (VEVRRA) and qualified individuals with disabilities under Section 503 of the Rehabilitation Act. We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations in accordance with applicable law.
